The Real Cost Factors of Business Analytics for Enterprises Or Teams

THE REAL COST FACTORS OF BUSINESS ANALYTICS (for Enterprises or Teams) INTRODUCTION

Analytics for teams and enterprise has become a mandatory element of any business strategy to improve competitive advantage and drive better business performance. As organizations strive to increase the availability, scalability and performance of their business analytics applications, it is becoming clear that the costs and complexity of business analytics extend beyond the initial software license acquisition.

The obvious way to view business analytics costs looks something like this: more software licenses for more people equals more money. In fact, licenses are commonly used as a red herring in analytics pricing models, but they turn out to be only a small part of the total cost. The greater impact on total cost of ownership (TCO) generally comes from fundamental software and hardware infrastructure choices, professional services, integration costs and, most of all, human capital.

Business analytics buyers have the opportunity to select a technology that minimizes staffing efforts and, consequently, reduces overall costs. The typical purchasing department concentrates on the initial analytics acquisition costs of a software license because these costs are often more immediate and easier to measure. It is critical to keep in mind that Gartner estimates that 92% of the money customers spend on analytics applications is spent after the initial deployment, on such items as staffing, integrations and maintenance.

1 LICENSE COSTS BACK-END SOFTWARE STACKS:

Provide only back-end functionality, like data storage, transformation and management (i.e., data warehouse and data mart functionality, ETL capabilities). Although license costs tend to be a small percentage of an entire analytics project, this tends to be where a customer’s procurement team and a vendor’s sales team focus most.

Many analytics vendors have complex licensing models that may or may not include upgrades and have role-based licenses or strict per-user restrictions that are easy to exceed as employees come ETL and go. The ﬁrst rule of thumb is to ensure that you are well versed on the exact terms of the licenses you are purchasing. It is not unusual to ﬁnd that the “full analytics suite” that was demoed is not DW included in the base price you are quoted. Optional modules that you may have assumed were standard may not actually be included, and so on. Make sure to review what is and, more important, is BACK-END STACK FULL-STACK ETL not included in the initial acquisition. INTEGRATION COSTS – FULL STACK VERSUS COMPONENTS Query/Import FRONT-END STACK

When evaluating the full TCO for analytics, it is important to take a full-stack view of the solution. Business analytics software can be broken down into two components that, when integrated eﬀectively, oﬀer a full analytics solution. Most vendors tend to focus on either a front-end or a back-end solution, but today there are industry leaders that provide a full-stack solution as well.

2 FRONT-END SOFTWARE STACKS: MULTIPLE PRODUCTS FROM MULTIPLE VENDORS:

Provide only front-end (end-user-facing) functionality, such as data visualization, You may decide to go with what is sometimes considered a “best of breed” solution and select data discovery and visual analysis. vendors that choose to focus on part of the analytics stack. These solutions tend to have a lower user license cost, but integrating between nonrelated tools is notoriously diﬃcult, especially if it FULL SOFTWARE STACKS: includes integrated tools that were not originally designed to be integrated. Add the integration costs to the costs of licenses and the time and hassle of dealing with multiple support desks and multiple training tracks, and the overall TCO can easily skyrocket. Software stacks that deliver both back-end and front-end functionalities.

In most cases, implementing only a back-end stack or a front-end stack would not suffice to INTEGRATED PRODUCTS: ensure a real, effective and scalable business analytics solution. When determining the TCO for analytics, you’ll need to consider not only your preference for partial- or full-stack breakdown of your Selecting a platform that was conceived and designed as an integrated product and receives configuration but also the integration costs of that choice. ongoing unified maintenance is guaranteed to simplify things and reduce TCO. Designed to work with seamless interoperability, integrated interfaces and coordinated, single-point support, an MULTIPLE PRODUCTS FROM A SINGLE VENDOR: integrated product will be simpler, more affordable, fully integrated and easier to implement.

Many of the leading products in the market are the result of corporate acquisitions, mergers and product integrations.

When a company integrates several products that have been bundled together to provide a full suite of services, the result is often overlapping, mismatched software suites that lack a seamless user experience. Often users are required to purchase licenses for each product individually. Not only is this cumbersome to purchase and manage, but it also increases the likelihood that the products will not be streamlined and integrated suﬃciently to provide a single point of knowledge.

3 SUBSCRIPTION VERSUS PERPETUAL Other factors to consider with a perpetual license include: Often includes additional mandatory fee of 18% to 20% of the initial purchase price for support, releases and upgrades Mandatory maintenance and upgrade contracts often have restrictions that limit the Traditionally, on premise software was sold perpetually and Software-as-a-Service software number of major upgrades was sold as a subscription, but today almost every software package is available as either a Gain peace of mind knowing the software is sitting on your servers, under your control subscription or a perpetual purchase. Choosing between pricing models can be daunting. If the analytics application is integrated with other applications, it is comforting to know that the investment was made on a platform that isn’t going anywhere anytime soon Some characteristics of subscription that make it appealing to many customers include:

Lower upfront cost Annual renewals, which encourage the software provider to demonstrate ongoing value and build a relationship with the customer Annual renewals also mean less commitment for the long term, which may make budgeting decisions easier Generally include support and maintenance costs built into the annual cost Minor and major upgrades are generally included in the annual cost It is important to keep in mind that subscription models may not be an option for some highly regulated industries. Not all vendors cover all regulatory requirements, from data protection to user security and access.

Perpetual license models become more attractive when looking at the long-term costs. Subscription models break even somewhere between three and four years, at which point a perpetual license becomes less expensive.

4 HARDWARE PROPRIETARY HARDWARE:

Some analytics software is designed to work on proprietary hardware only. Proprietary hardware is a separate and discrete hardware device with integrated software (firmware) specifically designed Depending on the capacity needs of your analytics to provide a particular computing resource. Proprietary hardware is not designed to allow the requirements, you’ll need to select the appropriate customers to change the software or flexibly reconfigure the hardware. Almost by definition, proprietary hardware is significantly more expensive than commodity hardware, but it is also hardware platform that will be able to scale when data able to handle more capacity. sets or user load grows beyond your initial expectations. The three types of hardware platform configurations DISTRIBUTED DATABASES: used for analytics are: When data sizes get too large, a distributed database may be the best solution. A distributed database may be stored in multiple computers located in the same physical location or may be COMMODITY HARDWARE: dispersed over a network of interconnected computers. A distributed database system consists of loosely coupled sites that share no physical components (such as disk, RAM and CPU). The cost Commodity hardware is described as the hardware available with an average amount of computing of a distributed database is generally less than that of proprietary hardware, as the resources and resources; it is not considered a “luxury car” in its field. Commodity hardware does not imply low cost may be shared with others in the database farm. quality but rather affordability. Here is a summary of hardware choices: Today’s advanced analytics technologies are now being designed to work on 64-bit commodity machines. By using modern chipsets to their fullest potential, it is now possible to run queries on Commodity Proprietary Distributed Hardware Hardware Databases terabytes of data for hundreds of users on just one of today’s commodity hardware boxes. Hardware Class Commodity Proprietary Commodity

Best Architecture 1 server 1 server Unlimited servers

Capacity Terabytes Terabytes Petabytes

Hardware Costs 4-5 figures 6-7 figures 5-6 figures

5 With the limited pool of qualified analytics experts available, outsourcing analytical professional PROFESSIONAL SERVICES services has become a popular alternative even though it tends to be more expensive, creates an even bigger bottleneck and decreases an organization’s level of control. There is often no other alternative but to give the reins to a team of analytics professionals who manage these projects To compete effectively in an increasingly data-driven world, remotely. Although the initial price quote for outsourcing these professional services may seem cheaper in the short run, it is not in these consultants’ best interests to make you independent of businesses need to leverage all the data that’s essential to their platform when you will no longer need their services and thus pay their fees. If you choose to their operations and invest in people and platforms to utilize purchase professional services directly from a vendor, be sure to understand your contractual obligations and make clear their delivery requirements. strategic insights from an ever-growing pool of data. Ideally, an organization will be able to utilize an existing in-house SELF-SERVICE ALTERNATIVES technical team to plan, launch and maintain its analytics platform. With user-friendly, low-maintenance and self-serve A growing trend in the business intelligence industry is the self-service analytics concept. When traditional analytics becomes too expensive or takes too long to implement, customers want tools analytics tools, a standard technical team without specialized to enable self- reliance. Analytics vendors understand that SMB and Enterprise customers alike are skill sets should be able to handle this additional load. looking for tools with improved user interfaces and friendlier UIs that will allow wider adoption and impact of data analytics. As analytics tools get easier to implement and utilize, the percentage of When solutions get more complex, hardware more expensive and integrations more demanding, companies effectively using analytics will grow, and the tools you can offer your customers to do you may find yourself incurring additional costs above and beyond the anticipated cost of hardware, their own analytics will grow with it. software and infrastructure. When you outgrow your own technical team’s abilities and capacity, you have two alternatives, both costly and challenging: hire specialized professionals to join your organization or outsource the project to Business Intelligence (BI) consultants who offer a full range of IT and professional consulting.

Unfortunately, the pool of analytics experts with the right mix of statistical and mathematical knowledge, a deep understanding of business processes, and industry knowledge is limited. If you are lucky enough to ﬁnd one of these gems, he or she will likely become the bottleneck with all project requests, improvements and adjustments that need to funnel through that resource.

6 HUMAN CAPITAL COMPLEXITY OF TECHNOLOGY

It is not of great insight to say that the complexity of your analytics solution will directly affect the cost you will incur. A complete portfolio solution that integrates real-time monitoring, As discussed, the largest cost component over the analytics lifetime is skilled personnel. reporting, analysis, dashboards, and a robust and scalable infrastructure will enable staff to be IDC estimates that ongoing staffing costs constitute 60%-86% of owning enterprise analytics more efficient and effective. With fewer components to buy, manage and support, an integrated software over a three-year period, while hardware and software each represent only 7%. solution makes it easier, faster and less costly to scale up to more users and out to more data and functionality. IN-HOUSE VERSUS OUTSOURCED ONGOING MAINTENANCE One of the common problems typical business analytics solutions suffer from is their heavy reliance on IT involvement to set up and maintain data warehousing and OLAP cubes and even The majority of human capital costs go toward maintaining ongoing operations after year one. create and customize reports. The IT department quickly becomes a bottleneck, and just as Ongoing staffing costs include creating new reports; ensuring the platform is available for use; quickly, the effectiveness of the analytics solution you paid so much for becomes reliant on your overseeing users, software, security and performance; and actually maintaining the analytics adding more IT people to tend to requests. system. The analytics platform’s efficiency levels directly impact the number of required staffing resources. Platforms that offer self-service alternatives will allow users to perform the majority of Some companies are turning to hosted analytics solutions which are hosted IT departments with design and analysis, thereby reducing the load on the IT team. an arsenal of homemade or third-party software. This alternative may be a viable solution and save some recruitment dollars if your solution is not very complicated. Though they save money on head count, hosted analytics solutions will probably not solve the IT bottleneck; an IT department located in a different city or country will not be as responsive as the in-house alternative.

7 CONCLUSION

Analytics platforms are an example of where the 80/20 rule applies.

You should anticipate the licensing, hardware and startup costs to be about 20% of your TCO, with ongoing maintenance, staﬃng and integrations accounting for the remaining 80%. Selecting an analytics platform with a simple and inclusive licensing model, user-friendly interface for a shorter learning curve, fewer IT requirements, and scalable commodity hardware will be your best bet to NEXT STEPS: lower the total cost of ownership.

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